# minimum¶

paddle. minimum ( x, y, name=None ) [source]

Compare two tensors and return a new tensor containing the element-wise minima. The equation is:

\[out = min(x, y)\]

Note

`paddle.minimum` supports broadcasting. If you want know more about broadcasting, please refer to user_guide_broadcasting .

Parameters
• x (Tensor) – the input tensor, it’s data type should be float32, float64, int32, int64.

• y (Tensor) – the input tensor, it’s data type should be float32, float64, int32, int64.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor. If x, y have different shapes and are “broadcastable”, the resulting tensor shape is the shape of x and y after broadcasting. If x, y have the same shape, its shape is the same as x and y.

Examples

```import paddle

x = paddle.to_tensor([[1, 2], [7, 8]])
y = paddle.to_tensor([[3, 4], [5, 6]])
print(res)
# Tensor(shape=[2, 2], dtype=int64, place=Place(cpu), stop_gradient=True,
#        [[1, 2],
#         [5, 6]])

x = paddle.to_tensor([[[1, 2, 3], [1, 2, 3]]])
print(res)
# Tensor(shape=[1, 2, 3], dtype=int64, place=Place(cpu), stop_gradient=True,
#        [[[1, 0, 3],
#          [1, 0, 3]]])

x = paddle.to_tensor([2, 3, 5], dtype='float32')
y = paddle.to_tensor([1, float("nan"), float("nan")], dtype='float32')